Bayesian Statistics
Final Project
Leonardo Stincone
17th June 2019
Description of the problem
In this project I analysed a dataset regarding deaths in Milan. The dataset contains, for each day between 1/01/1980 and 31/12/1989:
- the number of deaths occurred in Milan (
tot.mort); - the number of deaths for respiratory issues in Milan (
resp.mort).
We have for each day some explanatory variables too:
- the mean temperature (
mean.temp); - the relative humidity (
rel.humid); - the sulphur dioxide level in ambient air (
SO2); - the total suspended particles in ambient air (
TSP).
The dataset has been described in Vigotti, M.A., Rossi, G., Bisanti, L., Zanobetti, A. and Schwartz, J. (1996). Short term effect of urban air pollution on respiratory health in Milan, Italy, 1980-1989. Journal of Epidemiology and Community Health, 50, 71-75. and it has been analysed in Ruppert, D., Wand, M.P. and Carroll, R.J. (2003), Semiparametric Regression Cambridge University Press..
The aim of the project is to build a predictive model for tot.mort and resp.mort and to understand which are the variables that mostly affect the probability of death.
Explorative Data Analysis
Univariate descriptive analysis
Response variables
Milan population
Explanatory variables
Multivariate descriptive analysis
Seasonal effect
Mortality
